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TinyLLaVA-OpenELM-450M-SigLIP-0.89B

TinyLLaVA has released a family of small-scale Large Multimodel Models(LMMs), ranging from 0.55B to 3.1B. Our best model, TinyLLaVA-Phi-2-SigLIP-3.1B, achieves better overall performance against existing 7B models such as LLaVA-1.5 and Qwen-VL.

Here, we introduce TinyLLaVA-OpenELM-450M-SigLIP-0.89B, which is trained by the TinyLLaVA Factory codebase. For LLM and vision tower, we choose OpenELM-450M-Instruct and siglip-so400m-patch14-384, respectively. The dataset used for training this model is the The dataset used for training this model is the LLaVA dataset.

Execute the following test code:

P.S. TinyLLaVA Factory is an open-source modular codebase for small-scale LMMs with a focus on simplicity of code implementations, extensibility of new features, and reproducibility of training results. This code repository provides standard training&evaluating pipelines, flexible data preprocessing&model configurations, and easily extensible architectures. Users can customize their own LMMs with minimal coding effort and less coding mistake. TinyLLaVA Factory integrates a suite of cutting-edge models and methods.